Bayesian information fusion and multitarget tracking for maritime situational awareness

• DOI: 10.1049/iet-rsn.2019.0508
• Publication Date: 2020-10-27T02:19:29Z
• Authors: Domenico Gaglione; Giovanni Soldi; Florian Meyer; Franz Hlawatsch; Paolo Braca; Alfonso Farina; Moe Z. Win
• Keywords: Situation Awareness; Information fusion; Tracking (education); Sensor Fusion; Situation analysis; Situational ethics

The goal of maritime situational awareness (MSA) is to provide a seamless wide‐area operational picture ship traffic in coastal areas and the oceans real time. Radar central sensing modality for MSA. In particular, oceanographic high‐frequency surface‐wave (HFSW) radars are attractive surveying large sea at over‐the‐horizon distances, due their low environmental footprint power requirements. However, design not optimal challenging conditions prevalent MSA applications, thus calling development dedicated information fusion multisensor‐multitarget tracking algorithms. this study, authors show how problem can be formulated Bayesian framework efficiently solved by running loopy sum‐product algorithm on suitably devised factor graph. Compared previously proposed methods, approach advantageous terms estimation accuracy, computational complexity, implementation flexibility, scalability. Moreover, its performance further enhanced estimating unknown model parameters an online fashion fusing automatic identification system (AIS) data context‐based information. effectiveness algorithms demonstrated through experimental results based simulated as well HFSW radar AIS data.